Sas/ Python Developer
2 days ago
Canada
Iris Software Inc.
Full-time
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We have Immediate requirement with our Direct Client as SAS / Python Developer @ Toronto ON (Hybrid - 3 Days/Week).Title: SAS / Python Developer - T4 only.
Primary Skills: SAS, Python, Migration.
Description:
7+ years of Experience in SAS, PythonSeeking an experienced
SAS / Python Developer
to join data modernization and migration team. In this role, you will be responsible for analyzing, converting, optimizing, and modernizing legacy SAS-based analytical workflows, data steps, macros, and reports into scalable, production-ready Python environments. You will work closely with data architects, business stakeholders, and infrastructure teams to ensure code accuracy and parity during the transition.Key ResponsibilitiesCode Migration & Translation:
Interpret and convert legacy SAS programs (including Base SAS, DATA steps, SAS macros, and PROC SQL) into modular, efficient Python scripts.Data Processing & Pipelines:
Build, maintain, and optimize data ingestion, transformation, and processing pipelines using Python data manipulation libraries (pandas, NumPy) and SQL.Validation & Testing:
Perform side-by-side output validation and debugging between legacy SAS outputs and new Python implementations to ensure statistical and logical parity.Automation & Infrastructure:
Support Unix/Linux-based automation, schedule jobs via CRON or enterprise orchestrators, and work within containerized or cloud-based Anaconda/JupyterHub environments.Code Quality & Documentation:
Maintain clean version control using Git/GitHub, write unit tests, and produce thorough technical documentation for migrated pipelines.Required QualificationsEducation:
Bachelor’s or master’s degree in computer science, Data Engineering, Statistics, or a related quantitative field.SAS Experience:
3+ years of hands-on development with Base SAS, SAS Macros, and PROC SQLPython Experience:
2+ years of production Python development, with strong proficiency in pandas, data wrangling, and relational SQL.Environment & Tools:
Experience working in Anaconda environments, Git/GitHub, and Linux/Unix shell scripting.Analytical Skills:
Strong debugging, root-cause analysis, and side-by-side data validation capabilities.
Primary Skills: SAS, Python, Migration.
Description:
7+ years of Experience in SAS, PythonSeeking an experienced
SAS / Python Developer
to join data modernization and migration team. In this role, you will be responsible for analyzing, converting, optimizing, and modernizing legacy SAS-based analytical workflows, data steps, macros, and reports into scalable, production-ready Python environments. You will work closely with data architects, business stakeholders, and infrastructure teams to ensure code accuracy and parity during the transition.Key ResponsibilitiesCode Migration & Translation:
Interpret and convert legacy SAS programs (including Base SAS, DATA steps, SAS macros, and PROC SQL) into modular, efficient Python scripts.Data Processing & Pipelines:
Build, maintain, and optimize data ingestion, transformation, and processing pipelines using Python data manipulation libraries (pandas, NumPy) and SQL.Validation & Testing:
Perform side-by-side output validation and debugging between legacy SAS outputs and new Python implementations to ensure statistical and logical parity.Automation & Infrastructure:
Support Unix/Linux-based automation, schedule jobs via CRON or enterprise orchestrators, and work within containerized or cloud-based Anaconda/JupyterHub environments.Code Quality & Documentation:
Maintain clean version control using Git/GitHub, write unit tests, and produce thorough technical documentation for migrated pipelines.Required QualificationsEducation:
Bachelor’s or master’s degree in computer science, Data Engineering, Statistics, or a related quantitative field.SAS Experience:
3+ years of hands-on development with Base SAS, SAS Macros, and PROC SQLPython Experience:
2+ years of production Python development, with strong proficiency in pandas, data wrangling, and relational SQL.Environment & Tools:
Experience working in Anaconda environments, Git/GitHub, and Linux/Unix shell scripting.Analytical Skills:
Strong debugging, root-cause analysis, and side-by-side data validation capabilities.